Goal Setting is Often an Act of Desperation, Part II

January is a popular month to set new goals, so I decided to kick-off this year with a four-part series on this very topic. In Part I of the series, I proposed four conditions that organizations should understand prior to setting a goal.

Organizations should understand the capability of the system or process under study.
Organizations should understand variation within the system or process under study.
Organizations should understand if the system or process under study is stable.
Organizations should have a logical answer to the question, “By what method?”

Absent an understanding of these conditions, goals are too often “arbitrary and capricious.”

Filtering Out the Noise

Last month, I discussed the difference between information and knowledge by analogizing the two concepts to data ponds (information) and data streams (knowledge). A key idea in the transformation of information to knowledge is adding the element of time and visualizing the data in a tool called a process behavior chart. Part of the power of the process behavior chart (PBC) is its ability to filter out the noise in our data; the idea of filtering out data “noise” is the focus of this post.

Getting Better: Filtering Out the Noise

As schools consider how to restart in the fall, some are galvanizing their community to consider this an opportunity for reinvention, a way to rethink how we educate our young, while others simply want to get students back in the building and return as quickly and safely as possible to the normal that existed prior to the pandemic. Regardless of a school’s position on the spectrum from restart to reinvention, a more sophisticated manner in which to analyze student engagement and track efforts to improve engagement will be necessary.